ECMS as a realization of Pontryagin's minimum principle for HEV control
By L. Serrao, Simona Onori, Giorgio Rizzoni. American Control Conference, 2009
439 citations recorded by the source corpus.
Subfields: Automotive Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/edc427e3a9558fa424d1a30eec3520257a4df618
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Automotive Engineering
- Xiaosong Hu
- Scott Jason Moura
- Shaobo Xie
- Zongke Xin
- Fengchun Sun
- Dongpu Cao
- James Brighton
- Yeojun Kim
In Electrical and Electronic Engineering
- Xiaosong Hu
- Scott Jason Moura
- Fengchun Sun
- Dongpu Cao
- Shaobo Xie
- Zongke Xin
- Francesco Borrelli
- Yeojun Kim
Citations in the corpus
- Velocity Predictors for Predictive Energy Management in Hybrid Electric Vehicles (2015, background): “The ECMS is an instantaneous optimization for HEV energy management [4], [5].”
- Optimal Control of Hybrid Electric Vehicles Based on Pontryagin's Minimum Principle (2011, methodology): “From the similarity between the Hamiltonian and EFC, ECMS was described as being fundamentally linked to the Euler–Lagrange equation [14], [26].”
- An investigation on the effect of driver style and driving events on energy demand of a PHEV (2012, methodology): “Instantaneous fuel economy optimisation technique like ECMS are used in [9, 10].”
- Pontryagin’s Minimum Principle based model predictive control of energy management for a plug-in hybrid electric bus (2019, background): “Thus far, a number of power management strategies have been suggested including rule-based and fuzzy logic-based strategies [5-6], optimal control theory methods, such as global optimization [7-8] and instantaneous optimization [9], as well as a variety of evolutionary algorithms, including particle”
- A Pontryagin Minimum Principle-Based Adaptive Equivalent Consumption Minimum Strategy for a Plug-in Hybrid Electric Bus on a Fixed Route (2017, neutral): “Energies 2017, 10, 1379 2 of 22 optimization methods [4,5], and the artificial intelligence algorithm [6].”
- Control of Connected and Automated Vehicles: State of the Art and Future Challenges (2018, background): “The reader is referred to [84, 85, 86, 87] for details on the model assumptions, guarantees of optimality, implementation details, and performance in case the assumptions are violated.”
- Energy Management in Plug-in Hybrid Electric Vehicles: Recent Progress and a Connected Vehicles Perspective (2017, background): “PMP assumptions and equations derivation can be found in [53]–[55] and [43], which includes Lagrange multipliers.”